From Code to Execution: Decoding Apache Spark's Core Mechanics with Scala
Briefly

Apache Spark is crucial for batch and stream processing of massive data sets, offering rapid insights and real-time data processing.
The Driver in Apache Spark coordinates the workflow, allocates tasks into stages for distributed execution, and manages resources with the cluster manager.
Executors in Apache Spark function as worker nodes, executing tasks from the Driver, providing in-memory storage for RDDs, and sending outcomes back.
Read at Medium
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